--------------------------------------------------------------------------------------------------------
      name:  rep
       log:  /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict project/Co
> nflict-Nigeria/Observationaldata/R9-Acled/JCR replication/output/04_robustness_analysis.log
  log type:  text
 opened on:   7 Dec 2025, 15:20:29
r; t=0.00 15:20:29

. 
. 
. *--------------------------------------------------------------
. * 2. LOAD DATA
. *--------------------------------------------------------------
. use "${data}/R8_final.dta", clear
r; t=0.00 15:20:29

. *--------------------------------------------------------------
. * 3. COVARIATES & OUTCOME GROUPS
. *--------------------------------------------------------------
. 
. * Demographic / covariate groups
. global cvars_demographics ///
>     age gender ///
>     ib1.race_group ib1.religion ib1.urban_rural ib4.educ_group ///
>     emp_group safety fearing_crime ///
>     discuss_politics police_station soldiers_army piped_water
r; t=0.00 15:20:29

. 
. global cvars ///
>     age gender ///
>     race_group religion ///
>     urban_rural educ_group emp_group ///
>     safety fearing_crime ///
>     discuss_politics police_station soldiers_army piped_water
r; t=0.00 15:20:29

. 
. * Outcome Groups
. global outc demo_support auth_support demo_rated
r; t=0.00 15:20:29

. 
. //drop zdemo_support zauth_support
. 
. foreach v of varlist $outc {
  2.     quietly summarize `v'
  3.     generate z`v' = (`v' - r(min)) / (r(max) - r(min))
  4. }
(163 missing values generated)
(67 missing values generated)
(208 missing values generated)
r; t=0.00 15:20:29

. 
. * Main z-outcomes used in this file (Table A.6, etc.)
. global zoutcomes_gr1 zdemo_support zauth_support
r; t=0.00 15:20:29

. 
. * Quick checks
. summarize $cvars

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
         age |      7,588    36.72338    14.38811         18        112
      gender |      7,594    .4994733    .5000326          0          1
  race_group |      7,593    1.119189    .4543337          1          3
    religion |      7,554    2.067514    1.157157          1          5
 urban_rural |      7,594    1.539768    .4984488          1          2
-------------+---------------------------------------------------------
  educ_group |      7,560    1.992989    .9724767          1          4
   emp_group |      7,561    1.608517    .8627515          1          3
      safety |      7,574    1.516636    .7813524          1          3
fearing_cr~e |      7,581    1.451524    .7550564          1          3
discuss_po~s |      7,550    .8430464    .7249147          0          2
-------------+---------------------------------------------------------
police_sta~n |      7,594    .3664735    .4818727          0          1
soldiers_a~y |      7,594    .1232552    .3287516          0          1
 piped_water |      7,594     .537793    .4986025          0          1
r; t=0.00 15:20:29

. summarize $zoutcomes_gr1

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
zdemo_supp~t |      7,431    .6666667    .4714362          0          1
zauth_supp~t |      7,527     .759798    .2927741          0          1
r; t=0.00 15:20:29

. 
. ***************************************************************
. * 5. BALANCE TEST – Figure A.3
. ***************************************************************
. 
. * Treatment indicator(s)
. global treatments time_zero
r; t=0.00 15:20:29

. 
. * Clear any svy settings
. svyset, clear
r; t=0.00 15:20:29

. 
. * Entropy balancing weights for time_zero on main covariates
. //drop balance_zero
. ebalance time_zero $cvars, generate(balance_zero) targets(2)


Data Setup
Treatment variable:   time_zero
Covariate adjustment: age gender race_group religion urban_rural educ_group emp_group safety fearing_cri
> me discuss_politics police_station soldiers_army piped_water (1st order). age gender race_group religi
> on urban_rural educ_group emp_group safety fearing_crime discuss_politics police_station soldiers_army
>  piped_water (2nd order).

Optimizing...
Iteration 1: Max Difference = 9694.90517
Iteration 2: Max Difference = 3565.58361
Iteration 3: Max Difference = 1310.73818
Iteration 4: Max Difference = 481.241154
Iteration 5: Max Difference = 176.113196
Iteration 6: Max Difference = 63.898083
Iteration 7: Max Difference = 22.6670153
Iteration 8: Max Difference = 7.59536789
Iteration 9: Max Difference = 2.2473652
Iteration 10: Max Difference = .560874927
Iteration 11: Max Difference = .097658524
Iteration 12: Max Difference = .004685279
maximum difference smaller than the tolerance level; convergence achieved


Treated units: 4775    total of weights: 4775
Control units: 2661    total of weights: 4775


Before: without weighting

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+--------------------------------
         age |     36.95      207.5      .8236 |     36.45      206.5      .9806 
      gender |     .4997      .2501    .001257 |     .4983      .2501    .006764 
  race_group |     1.183      .3065      2.828 |     1.002    .002253      35.06 
    religion |     2.007      1.508      1.199 |     2.146      .9865      .6185 
 urban_rural |     1.628      .2337      -.529 |     1.387      .2374      .4621 
  educ_group |     1.885      .9754      .6312 |     2.182      .8351     .08943 
   emp_group |     1.498      .6464      1.151 |     1.814      .8612      .3766 
      safety |     1.556      .6474      .9717 |     1.446      .5344      1.289 
fearing_cr~e |     1.496      .6116      1.147 |     1.372      .4825      1.579 
discuss_po~s |     .8515      .5018      .2203 |     .8388      .5706      .2759 
police_sta~n |     .3585        .23        .59 |      .375      .2345      .5162 
soldiers_a~y |     .1085     .09673      2.518 |     .1454      .1243      2.012 
 piped_water |     .5003      .2501   -.001257 |     .6084      .2383     -.4442 


After:  balance_zero as the weighting variable

             |              Treat              |             Control             
             |      mean   variance   skewness |      mean   variance   skewness 
-------------+---------------------------------+--------------------------------
         age |     36.95      207.5      .8236 |     36.95      207.5      .9586 
      gender |     .4997      .2501    .001257 |     .4997      .2501    .001294 
  race_group |     1.183      .3065      2.828 |     1.183      .3062       2.83 
    religion |     2.007      1.508      1.199 |     2.007      1.507      1.119 
 urban_rural |     1.628      .2337      -.529 |     1.628      .2338     -.5278 
  educ_group |     1.885      .9754      .6312 |     1.885      .9754      .6634 
   emp_group |     1.498      .6464      1.151 |     1.499      .6469      1.149 
      safety |     1.556      .6474      .9717 |     1.556      .6472      .9708 
fearing_cr~e |     1.496      .6116      1.147 |     1.496      .6115      1.146 
discuss_po~s |     .8515      .5018      .2203 |     .8516      .5019      .2202 
police_sta~n |     .3585        .23        .59 |     .3586      .2301      .5899 
soldiers_a~y |     .1085     .09673      2.518 |     .1085     .09677      2.517 
 piped_water |     .5003      .2501   -.001257 |     .5005      .2501   -.002154 
r; t=0.34 15:20:30

. 
. svyset [pweight = balance_zero]

Sampling weights: balance_zero
             VCE: linearized
     Single unit: missing
        Strata 1: <one>
 Sampling unit 1: <observations>
           FPC 1: <zero>
r; t=0.00 15:20:30

. 
. * Clear stored estimates
. estimates clear
r; t=0.00 15:20:30

. 
. * Balance regressions: raw vs weighted
. foreach y of varlist $treatments {
  2.     quietly regress `y' $cvars_demographics
  3.     estimates store T0_`y'
  4.     
.     quietly svy: regress `y' $cvars_demographics
  5.     estimates store T1_`y'
  6. }
r; t=0.28 15:20:30

. 
. * Plot balance: Panel A (unweighted) vs Panel B (weighted)
. coefplot T0_time_zero || ///
>          T1_time_zero, ///
>     drop(_cons) xline(0, lpattern(solid)) ///
>     byopts(row(1)) levels(99 95) ///
>     bylabels("(A) Treatment all" "(B) Using weight") ///
>     mlabel(cond(@pval<.001, "***", ///
>            cond(@pval<.01, "**", ///
>            cond(@pval<.05, "*", "")))) ///
>     title(" ")
r; t=1.66 15:20:32

. 
. * Add titles for subplots
. addplot 1: , b1title("Treatment all", size(small)) norescaling
r; t=0.35 15:20:32

. addplot 2: , b1title("Using balance (entropy)") norescaling
r; t=0.31 15:20:32

. 
. * Save and export the balance graph
. graph save   "${graph}/balance_afro.gph", replace
(file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR replication/output/graphs/balance_afro.gph
    not found)
file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict project/Conflict-N
> igeria/Observationaldata/R9-Acled/JCR replication/output/graphs/balance_afro.gph saved
r; t=0.27 15:20:33

. graph export "${graph}/balance_afro.eps", replace
(file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR replication/output/graphs/balance_afro.eps
    not found)
file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR replication/output/graphs/balance_afro.eps
    saved as EPS format
r; t=0.05 15:20:33

. graph export "${graph}/balance_afro.pdf", as(pdf) replace
file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR replication/output/graphs/balance_afro.pdf
    saved as PDF format
r; t=0.23 15:20:33

. 
. ***************************************************************
. * 6. MAIN REGRESSION – Table A.6 (GTD, full sample)
. ***************************************************************
. 
. * Treatment indicator
. global treatments time_zero 
r; t=0.00 15:20:33

. 
. * Entropy balancing weights
. global zoutcomes zdemo_support zauth_support
r; t=0.00 15:20:33

. 
. capture erase "${table}/t1_e.xls"
r; t=0.00 15:20:33

. capture erase "${table}/t1_e.rtf"
r; t=0.00 15:20:33

. estimates clear
r; t=0.03 15:20:33

. eststo clear
r; t=0.00 15:20:33

. 
. * Make sure esttab / eststo / estadd are available
. cap which esttab
r; t=0.01 15:20:33

. if _rc ssc install estout, replace
r; t=0.00 15:20:33

. 
. local models
r; t=0.00 15:20:33

. 
. foreach k of varlist $zoutcomes {
  2.     
.     *--------------------------
.     * 1) Run model
.     *--------------------------
.     quietly svy: reg `k' i.time_zero $cvars i.cntrynum i.surveyyear
  3.     
.     *--------------------------
.     * 2) Control-group summary
.     *--------------------------
.     quietly summarize `k' if time_zero == 0
  4.     local m   = r(mean)
  5.     local min = r(min)
  6.     local max = r(max)
  7.     local dp  = 2
  8.     local fmt %`=`dp'+1'.`dp'f
  9. 
.     *--------------------------
.     * 3) Short titles for table
.     *--------------------------
.     local short_title ""
 10.     if "`k'" == "zdemo_support"    local short_title "Support for democracy"
 11.     if "`k'" == "zauth_support"    local short_title "Reject authoritarianism"
 12.  
. 
.     *--------------------------
.     * 4) Add custom stats to e()
.     *--------------------------
.     quietly estadd scalar cmean = `m'
 13.     quietly estadd scalar cmin  = `min'
 14.     quietly estadd scalar cmax  = `max'
 15.     quietly estadd local  pretreat "Yes"
 16. 
.     * Store model with nice title (for esttab)
.     eststo, title("`short_title'")
 17.     local models `"`models' `e(name)'"'
 18. 
.     *--------------------------
.     * 5) Export the same coeffs via outreg2
.     *--------------------------
.     outreg2 using "${table}/t1_e.xls", ///
>         keep(1.time_zero) ///
>         bracket bdec(3) sdec(3) alpha(0.01, 0.05) ///
>         ctitle(`k') label ///
>         addstat(Control Mean, `: display `fmt' `m'') ///
>         addtext(Covariates, Yes, Country FE, Yes, Survey Year FE, Yes) ///
>         nocons append
 19. }
(est1 stored)
/Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict project/Conflict-Nigeri
> a/Observationaldata/R9-Acled/JCR replication/output/tables/t1_e.xls
dir : seeout
(est2 stored)
/Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict project/Conflict-Nigeri
> a/Observationaldata/R9-Acled/JCR replication/output/tables/t1_e.xls
dir : seeout
r; t=0.79 15:20:34

.    
. 
. *------------------------------------------
. * PRINT TABLE TO RESULTS WINDOW
. *------------------------------------------
. esttab `models', ///
>     keep(1.time_zero) ///
>     b(3) se level(95) brackets ///
>     star(* 0.05 ** 0.01 *** 0.001) ///
>     label nonotes noobs nobaselevels ///
>     coeflabels(1.time_zero "Terrorism exposure") ///
>     mtitle ///
>     stats(N r2 pretreat cmean, ///
>           fmt(0 3 0 3 3 3) ///
>           labels("Observations" "R^2" "Pre-treatment" "Control Mean" "Min" "Max")) ///
>     compress

------------------------------------------
                       (1)          (2)   
                 Support~y    Reject ~m   
------------------------------------------
Terrorism expo~e    -0.051*      -0.045** 
                   [0.022]      [0.017]   
------------------------------------------
Observations          7293         7388   
R^2                  0.135        0.101   
Pre-treatment          Yes          Yes   
Control Mean         0.733        0.821   
------------------------------------------
r; t=0.08 15:20:34

. 
. *-------------------------------*
. * EXPORT CSV (same table)
. *-------------------------------*
. esttab `models' using "${table}/tableA6_gtd_fullsample.csv", replace csv ///
>     keep(1.time_zero) ///
>     coeflabels(1.time_zero "Terrorism exposure") ///
>     b(3) se level(95) brackets ///
>     star(* 0.05 ** 0.01 *** 0.001) ///
>     mtitle ///
>     label nonotes noobs nobaselevels ///
>     stats(N r2 pretreat cmean cmin cmax, ///
>           fmt(0 3 0 3 3 3) ///
>           labels("Observations" "R^2" "Pre-treatment" "Control mean" "Min" "Max")) ///
>     compress
(file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR
    replication/output/tables/tableA6_gtd_fullsample.csv not found)
(output written to /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict proj
> ect/Conflict-Nigeria/Observationaldata/R9-Acled/JCR replication/output/tables/tableA6_gtd_fullsample.c
> sv)
r; t=0.05 15:20:34

. ***************************************************************
. * 7. CROSS-COUNTRY REGRESSIONS – Figure A.4
. *    Afrobarometer Round 8 x GTD, 2019–2021
. ***************************************************************
. 
. ***************************************************************
. * RESTRICT SAMPLE: COUNTRIES WITH BOTH TREATED & CONTROL
. ***************************************************************
. preserve
r; t=0.09 15:20:34

.     gen flag_0 = (time_zero == 0)
r; t=0.00 15:20:34

.     gen flag_1 = (time_zero == 1)
r; t=0.00 15:20:34

. 
.     collapse (max) flag_0 flag_1, by(cntrynum)
r; t=0.15 15:20:34

. 
.     gen keep_country = (flag_0 == 1 & flag_1 == 1)
r; t=0.00 15:20:34

.     keep if keep_country
(9 observations deleted)
r; t=0.00 15:20:34

. 
.     keep cntrynum
r; t=0.00 15:20:34

.     tempfile good_cntryr8gtd
r; t=0.00 15:20:34

.     save `good_cntryr8gtd'
file /var/folders/xw/4b35bsn11yjdb9q5jx7fll_h0000gq/T//S_00928.000002 saved as .dta format
r; t=0.00 15:20:34

. restore
r; t=0.00 15:20:34

. 
. * Keep only countries that have both time_zero values
. merge m:1 cntrynum using `good_cntryr8gtd', keep(match) nogen
(label cntrynum already defined)

    Result                      Number of obs
    -----------------------------------------
    Not matched                             0
    Matched                             3,415  
    -----------------------------------------
r; t=0.00 15:20:34

. 
. * Save restricted dataset (used later for country plots)
. save "${data_new}/good_cntryr8gtd.dta", replace
(file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR replication/output/Generated
    data/good_cntryr8gtd.dta not found)
file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR replication/output/Generated
    data/good_cntryr8gtd.dta saved
r; t=0.03 15:20:34

. 
. //use "${data_new}/good_cntryr8gtd.dta", clear
. 
. * Outcomes for plots
. local outcome "zdemo_support zauth_support zdemo_rated"
r; t=0.00 15:20:34

. 
. * Get list of country codes actually in the restricted sample
. levelsof cntrynum, local(ctrylist)
1 3 5 8 11
r; t=0.01 15:20:34

. 
. local graphlist
r; t=0.00 15:20:34

. estimates clear
r; t=0.00 15:20:34

. 
. foreach cid of local ctrylist {
  2.     
.     * Get country name from value label, if available
.     local cname : label (cntrynum) `cid'
  3.     if "`cname'" == "" local cname "Country `cid'"
  4.     
.     local estlist
  5.     
.     * Run regressions per outcome for this country
.     foreach var of local outcome {
  6.         quietly capture svy: regress `var' i.time_zero $cvars i.surveyyear if cntrynum == `cid'
  7.         if !_rc {
  8.             estimates store est_`var'_`cid'
  9.             local estlist `estlist' est_`var'_`cid'
 10.         }
 11.     }
 12.     
.     * If at least one regression succeeded, draw a country plot
.     if "`estlist'" != "" {
 13.         local gname gr_`cid'
 14.         
.         capture noisily coefplot `estlist', ///
>             keep(1.time_zero) ///
>             drop(_cons) ///
>             xline(0, lcolor(gs10)) ///
>             coeflabels(1.time_zero = " ") ///
>                         plotlabels("Support for democracy" ///
>                        "Rejection of authoritarianism" ///
>                        "Democracy rating") ///
>             legend(rows(1)) ///
>             title("`cname'", size(medsmall)) ///
>             legend(off) ///
>             ylabel(, labsize(small)) ///
>             xlabel(-0.4(0.2)0.25, labsize(small)) ///
>             name(`gname', replace) ///
>             ysize(2) xsize(5)
 15.         
.         capture confirm graph `gname'
 16.         if !_rc {
 17.             local graphlist `graphlist' `gname'
 18.         }
 19.     }
 20. }
r; t=4.46 15:20:39

. 
. * Combine all successfully created graphs
.         grc1leg gr_1 gr_3 gr_5 gr_8 gr_11, ///
> cols(3) imargin(2 2 2 2) xsize(8) ysize(7)
r; t=3.36 15:20:42

. 
. graph save   "${graph}/DV1_cntryr8gtd.gph", replace
(file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR
    replication/output/graphs/DV1_cntryr8gtd.gph not found)
file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict project/Conflict-N
> igeria/Observationaldata/R9-Acled/JCR replication/output/graphs/DV1_cntryr8gtd.gph saved
r; t=0.76 15:20:43

. graph export "${graph}/DV1_cntryr8gtd.pdf", as(pdf) replace
file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR
    replication/output/graphs/DV1_cntryr8gtd.pdf saved as PDF format
r; t=0.02 15:20:43

. ***************************************************************
. * END OF DO-FILE
. ***************************************************************
. 
end of do-file

r; t=13.52 15:20:43
. do "/var/folders/xw/4b35bsn11yjdb9q5jx7fll_h0000gq/T//SD00928.000000"

. *----RUN this section after running the robustness results ----
. 
. * Figure 8: Cross-country regression – Afrobarometer Round 8 and GTD data,2019-2021
. graph use "${graph}/DV1_cntryr8gtd.gph"
r; t=3.20 15:21:20

. graph export "${graph}/DV1_cntryr8gtd.png", width(3000) replace
file /Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict
    project/Conflict-Nigeria/Observationaldata/R9-Acled/JCR
    replication/output/graphs/DV1_cntryr8gtd.png saved as PNG format
r; t=0.84 15:21:21

. putdocx paragraph, halign(center)
document not created
r(198); t=0.26 15:21:21

end of do-file

r(198); t=4.34 15:21:21

. do "/Users/souleymane.yameogo/Library/CloudStorage/Dropbox/WP3_OnlineCivics/Conflict project/Conflict-
> Nigeria/Observationaldata/R9-Acled/JCR replication/02_analysis.do"

. ***************************************************************
. * Afrobarometer R9 x ACLED – Cleaned, Replicable Pipeline
. * (copy–paste into a .do file)
. ***************************************************************
. //--------------------------------------------------------------
. // 02_analysis.do — Replication cleaning script
. // Project: "The Impact of Terrorism on Democratic Support in Africa"
. //--------------------------------------------------------------
. version 18.0
r; t=0.01 15:21:27

. clear all
r; t=0.27 15:21:27

. set more off
r; t=0.00 15:21:27

. set rmsg on
r; t=0.00 15:21:27

. cap set scheme plotplain
r; t=0.00 15:21:27

. 
. * --------------------------------------------------------------
. * Project root (robust to where the do-file is run from)
. * --------------------------------------------------------------
. local thisdo = c(filename)
r; t=0.00 15:21:27

. 
. * Fallback if c(filename) is empty (rare)
. if "`thisdo'" == "" {
.     global root "`c(pwd)'"
r; t=0.00 15:21:27
. }
r; t=0.00 15:21:27

. else {
.     * Directory containing this do-file
.     local dodir : dirname "`thisdo'"
r; t=0.00 15:21:27
.     * Project root is parent of /dofile
.     local root  : dirname "`dodir'"
r; t=0.00 15:21:27
.     global root "`root'"
r; t=0.00 15:21:27
. }
r; t=0.00 15:21:27

. 
. * If someone runs from inside /dofile (extra safety)
. if substr("${root}", -6, 6) == "dofile" {
.     global root = substr("${root}", 1, length("${root}")-6)
r; t=0.00 15:21:27
. }
r; t=0.00 15:21:27

. 
. *--------------------------------------------------------------
. * 0. PATHS (relative; no machine-specific paths)
. *--------------------------------------------------------------
. 
. global data   "${root}/Original data"
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. global do     "${root}/dofile"
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. global out    "${root}/output"
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. global table  "${out}/tables"
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. global graph  "${out}/graphs"
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. global data_new  "${out}/Generated data"
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. 
. cap mkdir "${out}"
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. cap mkdir "${table}"
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. cap mkdir "${graph}"
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. cap mkdir "${data_new}"
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. 
. cap log close _all
